Set of robotic environments based on PyBullet physics engine and gymnasium.
Project description
panda-gym
Set of robotic environments based on PyBullet physics engine and gymnasium.
Documentation
Check out the documentation.
Installation
Using PyPI
pip install panda-gym
From source
git clone https://github.com/qgallouedec/panda-gym.git
pip install -e panda-gym
Usage
import gymnasium as gym
import panda_gym
env = gym.make('PandaReach-v3', render_mode="human")
observation, info = env.reset()
for _ in range(1000):
action = env.action_space.sample() # random action
observation, reward, terminated, truncated, info = env.step(action)
if terminated or truncated:
observation, info = env.reset()
env.close()
You can also
Environments
PandaReach-v3 |
PandaPush-v3 |
 |
 |
PandaSlide-v3 |
PandaPickAndPlace-v3 |
 |
 |
PandaStack-v3 |
PandaFlip-v3 |
 |
 |
Baselines results
Baselines results are available in rl-baselines3-zoo and the pre-trained agents in the Hugging Face Hub.
Citation
Cite as
@article{gallouedec2021pandagym,
title = {{panda-gym: Open-Source Goal-Conditioned Environments for Robotic Learning}},
author = {Gallou{\'e}dec, Quentin and Cazin, Nicolas and Dellandr{\'e}a, Emmanuel and Chen, Liming},
year = 2021,
journal = {4th Robot Learning Workshop: Self-Supervised and Lifelong Learning at NeurIPS},
}
Environments are widely inspired from OpenAI Fetch environments.
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